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Happiness

Can you measure happiness? More importantly, assuming you can measure happiness, can you control happiness through measurable parameters? And even more importantly, assuming you can control happiness through measurable parameters, how much control do you have over those parameters versus the control your environment has?

A very interesting computational model tries to explore this above question.

And we at Cogent, have been doing our own research on Happiness in a totally different context (Employee Happiness). Needless to say, this is exactly why this study caught our eyes.

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The subjective well-being or happiness of individuals is an important metric for societies. Although happiness is influenced by life circumstances and population demographics such as wealth, we know little about how the cumulative influence of daily life events are aggregated into subjective feelings. Using computational modeling, we show that emotional reactivity in the form of momentary happiness in response to outcomes of a probabilistic reward task is explained not by current task earnings, but by the combined influence of recent reward expectations and prediction errors arising from those expectations. The robustness of this account was evident in a large-scale replication involving 18,420 participants. Using functional MRI, we show that the very same influences account for task-dependent striatal activity in a manner akin to the influences underpinning changes in happiness.